Literature DB >> 11497639

Clustering and preferential attachment in growing networks.

M E Newman1.   

Abstract

We study empirically the time evolution of scientific collaboration networks in physics and biology. In these networks, two scientists are considered connected if they have coauthored one or more papers together. We show that the probability of a pair of scientists collaborating increases with the number of other collaborators they have in common, and that the probability of a particular scientist acquiring new collaborators increases with the number of his or her past collaborators. These results provide experimental evidence in favor of previously conjectured mechanisms for clustering and power-law degree distributions in networks.

Year:  2001        PMID: 11497639     DOI: 10.1103/PhysRevE.64.025102

Source DB:  PubMed          Journal:  Phys Rev E Stat Nonlin Soft Matter Phys        ISSN: 1539-3755


  101 in total

1.  Scientific Networks on Data Landscapes: Question Difficulty, Epistemic Success, and Convergence.

Authors:  Patrick Grim; Daniel J Singer; Steven Fisher; Aaron Bramson; William J Berger; Christopher Reade; Carissa Flocken; Adam Sales
Journal:  Episteme (Edinb)       Date:  2013-12-01

Review 2.  Complex networks and simple models in biology.

Authors:  Eric de Silva; Michael P H Stumpf
Journal:  J R Soc Interface       Date:  2005-12-22       Impact factor: 4.118

3.  Asymmetric disassembly and robustness in declining networks.

Authors:  Serguei Saavedra; Felix Reed-Tsochas; Brian Uzzi
Journal:  Proc Natl Acad Sci U S A       Date:  2008-10-20       Impact factor: 11.205

4.  A maximum entropy framework for nonexponential distributions.

Authors:  Jack Peterson; Purushottam D Dixit; Ken A Dill
Journal:  Proc Natl Acad Sci U S A       Date:  2013-12-02       Impact factor: 11.205

Review 5.  Dual-phase evolution in complex adaptive systems.

Authors:  Greg Paperin; David G Green; Suzanne Sadedin
Journal:  J R Soc Interface       Date:  2011-01-19       Impact factor: 4.118

6.  Likelihood-based approach to discriminate mixtures of network models that vary in time.

Authors:  Naomi A Arnold; Raul J Mondragón; Richard G Clegg
Journal:  Sci Rep       Date:  2021-03-04       Impact factor: 4.379

7.  Simplicial closure and higher-order link prediction.

Authors:  Austin R Benson; Rediet Abebe; Michael T Schaub; Ali Jadbabaie; Jon Kleinberg
Journal:  Proc Natl Acad Sci U S A       Date:  2018-11-09       Impact factor: 11.205

8.  Network science: Luck or reason.

Authors:  Albert-László Barabási
Journal:  Nature       Date:  2012-09-12       Impact factor: 49.962

9.  Social structures depend on innate determinants and chemosensory processing in Drosophila.

Authors:  Jonathan Schneider; Michael H Dickinson; Joel D Levine
Journal:  Proc Natl Acad Sci U S A       Date:  2012-07-16       Impact factor: 11.205

10.  The Mycobacterium tuberculosis drugome and its polypharmacological implications.

Authors:  Sarah L Kinnings; Li Xie; Kingston H Fung; Richard M Jackson; Lei Xie; Philip E Bourne
Journal:  PLoS Comput Biol       Date:  2010-11-04       Impact factor: 4.475

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